Certain types of rare cells circulating in the bloodstream (rare circulating cells, RCCs) have recently emerged as highly promising biomarker candidates in a growing number of disease conditions. For example, Circulating Tumor Cells (CTCs) are considered promising diagnostic and prognostic markers for the monitoring of cancer progression and anti-cancer treatment responses. Moreover, Circulating Endothelial Cells (CECs) are considered promising diagnostic and prognostic markers in cardiovascular disease conditions, such as acute myocardial infarction.
RCCs can be conveniently collected in blood samples (“liquid biopsy”), which enables repeated sampling throughout the course of a patient's disease progression or treatment regimen. Consequently, diagnostic methods based on RCC detection, quantification and analysis enable the real-time and personalized assessment of an individual patient's disease, which facilitates the design of personalized treatment plans.
However, the development of full biomarker utility of RCCs has been hindered by the lack of assay technologies that can accurately and robustly identify and enumerate RCCs and also allow for the downstream analysis of RCC cell biology (e.g., gene expression, metabolic activity, protein localization, RNA localization) and RCC molecular biology (e.g., genome, proteome, secretome, metabolome analysis). Especially the extremely low abundance of RCCs and the tremendous heterogeneity of RCC populations have posed substantial technical challenges for the development of reliable diagnostic assays.
Most existing RCC assay platforms lack the sensitivity and accuracy to allow for robust RCC identification and quantification. Moreover, the vast majority of RCC assay platforms do not allow for the detailed cellular or molecular analysis of RCCs once these cells have been identified and enumerated.
For example, many methods for RCC identification and quantification rely on flow cytometry (e.g., FACS) or immunocapture technologies (e.g., CellSearch®). While flow cytometry generally enables cell sorting, it cannot robustly enumerate very small populations of cells, such as CTCs or CECs (˜1-10 CTCs/ml whole blood), in the presence of much more abundant cell populations, such as the white blood cell population (WBC; >1 million CTCs/ml whole blood). Additionally, FACS-based methods do not allow for the indepth analysis of cell morphologies.
One prominent example of RCC immunocapture platforms is the CellSearch® platform, which has obtained FDA-approval for the monitoring of metastatic cancer patients. The CellSearch® CTC immunocapture assay has recently been adapted for CEC detection (see, e.g., Damani, et al., 2012, Sci. Tansl. Med. 4, 126 ra33). However, CellSearch® and related immunocapture platforms require an initial immunomagnetic bead-based capture step that targets a single biomarker to enrich the very rare RCCs in a sample prior to an attempted identification and quantification. It is this initial, targeted enrichment step that render an unbiased multi-parametric analysis and classification of heterogeneous RCC populations impossible and that prevents any analysis from reaching much beyond the analysis of the single biomarker used for cell capture. Moreover, RCC-targeted immunocapture assays are often plagued by a lack of assay sensitivity and specificity.
Due to the limitations of many existing assay technologies, the RCC levels reported for human blood samples vary greatly across the literature, even though substantial assay optimization and standardization efforts were made. This variability in RCC assay results significantly impedes the further development of RCCs as clinically useful biomarkers. Another caveat of most existing RCC assay technologies is the limited amount of diagnostically relevant information that is commonly obtained. Typical RCC assays may deliver RCC counts and describe general morphological features of a cell (e.g., cell size, size distributions across a cell population), but current RCC assays typically do not provide a diagnostically meaningful profile of RCC cell biology (e.g., regarding the energy metabolism of cancer cells or the presence of apoptotic bodies) or RCC molecular biology (e.g., presence of genetic abnormalities, including gene fusions, aneuploidy, loss of chromosomal regions, specific oncogene mutations or oncogene expression levels). Thus, new approaches are needed to accurately identify, enumerate and analyze RCCs.
Recently, a high-definition (HD) immunofluorescence assay platform has been developed, which enables the reliable identification and enumeration of RCCs in the presence of much more abundant cell types. HD-RCC assays are generally based on the side-by-side comparison of rare cells (e.g., CTCs or CECs) and abundant cells (e.g., WBCs) in non-enriched samples (e.g., blood samples) with respect to certain immunofluorescent and morphological characteristics. Most notably, HD-CTC and HD-CEC assays have proven to enable the highly sensitive, highly accurate, and highly robust detection and quantification of CTCs and CECs.
While current HD-RCC assay protocols enable accurate cell identification and cell counting, robust protocols for the subsequent downstream analysis of RCC cell biology or RCC molecular biology are still largely lacking today. Nevertheless, it is widely expected that a deeper understanding of RCC biology will promote the development of meaningful disease diagnostics and efficacious treatments. For example, it is expected that a better understanding of CTC biology will promote the development of next-generation anti-cancer treatments that target CTCs and thereby help suppress tumor metastasis. Moreover, it is expected that the detection of certain molecular characteristics of CTCs will have immediate diagnostic value (e.g., detection of BRCA-1/2 mutations) and aid in the personalized tailoring of anti-cancer treatment regimens to each patient (e.g., treatment with PARP inhibitors).
Thus, there exists a need for methods enabling the cellular and molecular analysis of RCCs following RCC detection. The present disclosure addresses this need by providing methods for the analysis of RCCs in non-enriched patient samples. Related advantages are provided as well.